• 제목/요약/키워드: polynomial approximation

검색결과 216건 처리시간 0.027초

A SIMULTANEOUS NEURAL NETWORK APPROXIMATION WITH THE SQUASHING FUNCTION

  • Hahm, Nahm-Woo;Hong, Bum-Il
    • 호남수학학술지
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    • 제31권2호
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    • pp.147-156
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    • 2009
  • In this paper, we actually construct the simultaneous approximation by neural networks to a differentiable function. To do this, we first construct a polynomial approximation using the Fejer sum and then a simultaneous neural network approximation with the squashing activation function. We also give numerical results to support our theory.

QUASI-INTERPOLATORY APPROXIMATION SCHEME FOR MULTIVARIATE SCATTERED DATA

  • Yoon, Jung-Ho
    • Journal of applied mathematics & informatics
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    • 제29권3_4호
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    • pp.713-719
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    • 2011
  • The problem of approximation from a set of scattered data arises in a wide range of applied mathematics and scientific applications. In this study, we present a quasi-interpolatory approximation scheme for scattered data approximation problem, which reproduces a certain space of polynomials. The proposed scheme is local in the sense that for an evaluation point, the contribution of a data value to the approximating value is decreasing rapidly as the distance between two data points is increasing.

이동하는 음원에 적합한 고분해능 광대역 LPA 빔형성기법 (High Resolution Wideband Local Polynomial Approximation Beamforming for Moving Sources)

  • 박도현;박규태;이정훈;이수형;이균경
    • 한국음향학회지
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    • 제24권1호
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    • pp.1-10
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    • 2005
  • 본 논문에서는 이동하는 광대역 음원의 위치추정에 적합한 높은 분해능을 가지는 광대역LPA (local polynomial approximation) 빔형성기법을 제안한다. 제안한 기법은 여러 개의 데이터 단편으로부터 구하는 공분산행렬 대신, 하나의 데이터 단편의 여러 개 주파수 성분으로부터 얻은 조향 공분산행렬을 이용하는 STMV(steered minimum variance) 기법을 LPA 빔형성기법에 적용하였다. STMV 기법의 센서가중벡터를 이용하여 LPA 가격함수를 구성하였으며 이를 최대화 시키는 방위각과 각속도를 2차원 탐색을 통하여 추정함으로써 높은 방위각 분해능을 가지도록 하였다. 모의신호와 실제 해상 실험 데이터를 이용하여 제안한 기법의 성능을 기존의 기법과 비교, 분석 하였다

유리분수함수 근사법에 기반한 풍하중을 받는 구조물의 동특성 추정 (Modal Parameter Estimations of Wind-Excited Structures based on a Rational Polynomial Approximation Method)

  • 김상범;이완수;윤정방
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2005년도 추계학술대회논문집
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    • pp.287-292
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    • 2005
  • This paper presents a rational polynomial approximation method to estimate modal parameters of wind excited structures using incomplete noisy measurements of structural responses and partial measurements of wind velocities only. A stochastic model of the excitation wind force acting on the structure is estimated from partial measurements of wind velocities. Then the transfer functions of the structure are approximated as rational polynomial functions. From the poles and zeros of the estimated rational polynomial functions, the modal parameters, such as natural frequencies, damping ratios, and mode shapes are extracted. Since the frequency characteristics of wind forces acting on structures can be assumed as a smooth Gaussian process especially around the natural frequencies of the structures according to the central limit theorem (Brillinger, 1969; Yaglom, 1987), the estimated modal parameters are robust and reliable with respect to the assumed stochastic input models. To verify the proposed method, the modal parameters of a TV transmission tower excited by gust wind are estimated. Comparison study with the results of other researchers shows the efficacy of the suggested method.

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다항식회귀분석을 이용한 기능성곡면의 모델링 (Modeling of functional surface using Polynomial Regression)

  • 윤상환;황종대;정윤교
    • 한국공작기계학회:학술대회논문집
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    • 한국공작기계학회 2002년도 추계학술대회 논문집
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    • pp.376-380
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    • 2002
  • This research presents modeling of a functional surface which is a constructed free-formed surface. The modeling introduced in this paper adopts polynomial regression that is utilizing approximating technique. The measured data are obtained from measuring with Coordinate Measuring Machine. This paper introduces efficient methods of Reverse Engineering using Polynomial Regression.

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다항식 근사를 이용한 심전도 분석 및 원격 모니터링 (Polynomial Approximation Approach to ECG Analysis and Tele-monitoring)

  • 유기호;정구영;정성남;노태수
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2001년도 춘계학술대회논문집B
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    • pp.42-47
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    • 2001
  • Analyzing the ECG signal, we can find heart disease, for example, arrhythmia and myocardial infarction, etc. Particularly, detecting arrhythmia is more important, because serious arrhythmia can take away the life from patients within ten minutes. In this paper, we would like to introduce the signal processing for ECG analysis and the device made for wireless communication of ECG data. In the signal processing, the wavelet transform decomposes the ECG signal into high and low frequency components using wavelet function. Recomposing the high frequency bands including QRS complex, we can detect QRS complex and eliminate the noise from the original ECG signal. To recognize the ECG signal pattern, we adopted the polynomial approximation partially and statistical method. The ECG signal is divided into small parts based on QRS complex, and then, each part is approximated to the polynomials. Comparing the approximated ECG pattern with the database, we can detect and classify the heart disease. The ECG detection device consists of amplifier, filters, A/D converter and RF module. After amplification and filtering, the ECG signal is fed through the A/D converter to be digitalized. The digital ECG data is transmitted to the personal computer through the RF transceiver module and serial port.

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퍼지 결합 다항식 뉴럴 네트워크 (Fuzzy Combined Polynomial Neural Networks)

  • 노석범;오성권;안태천
    • 전기학회논문지
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    • 제56권7호
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    • pp.1315-1320
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    • 2007
  • In this paper, we introduce a new fuzzy model called fuzzy combined polynomial neural networks, which are based on the representative fuzzy model named polynomial fuzzy model. In the design procedure of the proposed fuzzy model, the coefficients on consequent parts are estimated by using not general least square estimation algorithm that is a sort of global learning algorithm but weighted least square estimation algorithm, a sort of local learning algorithm. We are able to adopt various type of structures as the consequent part of fuzzy model when using a local learning algorithm. Among various structures, we select Polynomial Neural Networks which have nonlinear characteristic and the final result of which is a complex mathematical polynomial. The approximation ability of the proposed model can be improved using Polynomial Neural Networks as the consequent part.

컴퓨터 처리를 위한 대규모 시스템의 간략법에 관한 연구 (A Study on the Large Scale Systems Simplification for computer processing)

  • 황형수;권오신;이창구
    • 대한전기학회논문지
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    • 제36권4호
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    • pp.280-286
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    • 1987
  • A new method is presented for obtaining redced-order model for time-invariant systems. This method does not require the calculation of the reciprocal transformation, the alpha table, the beta-table and the alpha-beta expansion which should be calculated in Routh approximation method, hence it is computationally very attractive better than Routh approximation method, furthemore the stability of the reduced-order model is guaranted if the original system is stable. This method starts with the continued fraction espansion of auxiliary denominator polynomial give for the denominator polynomial of the reduced-order model. The coefficients of the numerator polynomial are then obtained by equating moment of the original and the reduced-order medel.

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초정밀 구조해석을 위한 수치절차의 영향 분석 (Investigation of the Effects of Some Numerical Procedure on the High Precision Structural Analysis)

  • 정강식;유홍희
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2004년도 춘계학술대회
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    • pp.756-761
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    • 2004
  • The effects of two important numerical procedures on the high precision structural analysis are investigated in this study. The two numerical procedures include continuous variable approximation and time integration. For the continuous variable approximation, polynomial mode functions generated by the Gram-Schmidt process are introduced and the numerical results obtained by employing the polynomial mode functions are compared to those obtained by classical beam mode functions. The effect of the time integration procedure on the analysis precision is also investigated. It is found that the two procedures affect the precision of structural analysis significantly.

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Efficient Piecewise-Cubic Polynomial Curve Approximation Using Uniform Metric

  • Kim, Jae-Hoon
    • Journal of information and communication convergence engineering
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    • 제6권3호
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    • pp.320-322
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    • 2008
  • We present efficient algorithms for solving the piecewise-cubic approximation problems in the plane. Given a set D of n points in the plane, we find a piecewise-cubic polynomial curve passing through only the points of a subset S of D and approximating the other points using the uniform metric. The goal is to minimize the size of S for a given error tolerance $\varepsilon$, called the min-# problem, or to minimize the error tolerance $\varepsilon$ for a given size of S, called the min-$\varepsilon$ problem. We give algorithms with running times O($n^2$ logn) and O($n^3$) for both problems, respectively.